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Aquarium scores $2.6M seed to refine machine learning model data

TechCrunch

Aquarium , a startup from two former Cruise employees, wants to help companies refine their machine learning model data more easily and move the models into production faster. One customer Sterblue offers a good example. investment to build intelligent machine learning labeling platform. The Aquarium team.

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List of Top 10 Machine Learning Examples in Real Life

Openxcell

But with technological progress, machines also evolved their competency to learn from experiences. This buzz about Artificial Intelligence and Machine Learning must have amused an average person. But knowingly or unknowingly, directly or indirectly, we are using Machine Learning in our real lives.

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Colorado AI legislation further complicates compliance equation

CIO

The bill does not limit AI’s definition to any specific area, such as generative AI, large language models (LLMs), or machine learning. Robert] Rodriguez on this important issue and will review the final language of the bill when it reaches his desk,” said Eric Maruyama, the governor’s deputy press secretary.

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Butter raises $7M to end ‘accidental’ customer churn due to payment failure

TechCrunch

It was there that he realized there was an astounding number of subscriptions that failed to renew or even go through to begin with due to payment-related issues. The accidental churn is often not just due to problems with renewals, where people get frustrated by failed attempts to charge their credit card, for example.

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Why you should care about debugging machine learning models

O'Reilly Media - Data

For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. Model debugging is an emergent discipline focused on finding and fixing problems in ML systems. We’ll review methods for debugging below. Not least is the broadening realization that ML models can fail.

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Evolving from Rule-based Classifier: Machine Learning Powered Auto Remediation in Netflix Data…

Netflix Tech

Given the extensive scope and intricate complexity inherent to such a distributed, large-scale system, even if the failed jobs account for a tiny portion of the total workload, diagnosing and remediating job failures can cause considerable operational burdens. Therefore, the operational cost increases linearly with the number of failed jobs.

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Machine Learning for Fraud Detection in Streaming Services

Netflix Tech

Data analysis and machine learning techniques are great candidates to help secure large-scale streaming platforms. In semi-supervised anomaly detection models, only a set of benign examples are required for training. a browser) is normally matched with a certain DRM system (e.g.,